Epidemiology

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# Epidemiology
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.author[
### Claire Prince • 04-Nov-2022
]
.institute[
### Zifo RnD Solutions
]

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## What is epidemiology
 
“The study of the distribution and determinants of disease in health-related states and events in defined populations, and the application of this study to the control of health problems”
 
Last J. Dictionary of epidemiology, OUP, 2001
 
<img src="data:image/png;base64,#data/epidemiology/whatisepi.png" width="70%" style="display: block; margin: auto;" />

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## Epidemiological studies

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## Evaluating rates of disease

* Incidence 
 
 + The rate at which **new** cases occur in a population during a specified period.

* Prevalence
 
 + The proportion of **existing** cases in a population at one point in time.

* Attributable proportion
 
 + The proportion of a disease in a group that is exposed to a **particular factor** which can be attributed to their exposure to that factor. 
 
* Risk ratio
 
 + Ratio of the probability of an event occurring in the **exposed** population to the probability of it occurring in the **unexposed** population
 
* Incidence rate ratio
 
 + Ratio of the incidence rate of disease in the **exposed** population compared to that in the **unexposed** population

* Odds ratio
 
 + Odds of an event is the probability that an individual **experiences the event** divided by the probability that **they do not**.

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## Calculating odds and risk ratios

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## Diagnostic tests

* The **sensitivity** of a test is the proportion of people who test **positive** among all those who **actually have the disease**.
 
* The **specificity** of a test is the proportion of people who test **negative** among all those who **actually do not have that disease**.
 
* The **positive predictive value** is the **probability** that following a **positive** test result, that individual will **truly have that disease**.
 
* The **negative predictive value** is the **probability** that following a **negative** test result, that individual will **truly not have that disease**.
 
<img src="data:image/png;base64,#data/epidemiology/diagtests.png" width="60%" style="display: block; margin: auto;" />

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## Measurement error and bias

* Selection bias
 
* Information bias
 
 + Recall bias
 
 + Observer bias
 
* Consequences of information bias
 
 + Non-differential misclassifcation
 
 + Differential misclassification

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## Confounding/mediation
 
<img src="data:image/png;base64,#data/epidemiology/confoud-mediate.png" width="80%" style="display: block; margin: auto;" />
 
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## Confounding
 
* A **confounder** is a variable that influences both the exposure and outcome, causing a spurious association
 
<img src="data:image/png;base64,#data/epidemiology/confound.png" width="80%" style="display: block; margin: auto;" />

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## Mediation
 
* A **mediator** is a variable that is influenced by the exposure and in turn influences the outcome.
 
<img src="data:image/png;base64,#data/epidemiology/mediate.png" width="80%" style="display: block; margin: auto;" />

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## Genetic epidemiology
 
* Understanding how genetic factors influence traits and disease.
 
* Twin studies
 
* Linkage analysis
 
* Association

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## Twin studies

* Comparison of monozygotic and dizygotic twins
 
<img src="data:image/png;base64,#data/epidemiology/twins.png" width="100%" style="display: block; margin: auto;" />

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## Linkage analysis

* Within family analysis used to identify **rare variants** that influence rare disease.
 
<img src="data:image/png;base64,#data/epidemiology/linkage.png" width="90%" style="display: block; margin: auto;" />

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## Genome wide association studies
 
* Test associations between **genetic variants** and a specific trait and disease
 
* In GWAS' the most tested genetic variants are **single-nucleotide polymorphisms** (SNPs)
 
<img src="data:image/png;base64,#data/epidemiology/GWAS.png" width="50%" style="display: block; margin: auto;" />

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## GWAS quality control
 
<img src="data:image/png;base64,#data/epidemiology/gwasqc.png" width="100%" style="display: block; margin: auto;" />

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## GWAS steps
 
<img src="data:image/png;base64,#data/epidemiology/gwassteps.png" width="70%" style="display: block; margin: auto;" />

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## Current GWAS limitations
 
* Most published GWAS’ are performed in individuals of European descent
 
* Variants identified for a specific complex trait or disease only account for a **small proportion** of the estimated heritability
 
* Doesn’t necessarily identify **causal** variants and genes
 
* Limited clinical predictive value

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## Beyond GWAS
 
* Statistical fine-mapping
 
* SNP enrichment
 
* Quantitative trait loci mapping
 
* Colocalization
 
* Functional studies
 
* Clinical significance
<img src="data:image/png;base64,#data/epidemiology/beyondgwas.png" width="60%" style= "float:right;position: relative; top: -420px;" style="display: block; margin: auto;" />
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## Other 'omics
 
<img src="data:image/png;base64,#data/epidemiology/omics.png" width="70%" style="display: block; margin: auto;" />

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## Epigenome
 
<img src="data:image/png;base64,#data/epidemiology/epigenome.png" width="80%" style="display: block; margin: auto;" />

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## Transcriptome wide association studies

* A gene-based association approach that investigates associations between **genetically regulated gene expression** and complex diseases or traits.
 
<img src="data:image/png;base64,#data/epidemiology/twas.png" width="90%" style="display: block; margin: auto;" />

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## Mendelian randomization

* A method that uses genetic variants as instrumental variables to explore causal effects of risk factors on outcomes in observational epidemiological studies.

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## Mendelian randomization

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## Summary

* Epidemiology is “The study of the distribution and determinants of disease in health-related states and events in defined populations, and the application of this study to the control of health problems”
 
* Genetic epidemiology allow us to understand the genetic risk factors for health traits and disease
 
* There are methods that utilise GWAS findings to prioritize variants for further study which may lead to clinical significance
 
* Other 'omics such as the epigenome and transcriptome can be studies to aid in the understanding of disease in populations
 
* Mendelian randomization uses GWAS with the aim to isolate causal effects by avoiding confoundings and reverse causation.

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## Further reading
* Epidemiology for the uninitiated. From: https://www.bmj.com/about-bmj/resources-readers/publications/epidemiology-uninitiated
* Paternoster L, Tilling K, Davey Smith G. Genetic epidemiology and Mendelian randomization for informing disease therapeutics: Conceptual and methodological challenges. PLoS Genet. 2017 Oct 5;13(10):e1006944.
* Tam V, Patel N, Turcotte M, Bossé Y, Paré G, Meyre D. Benefits and limitations of genome-wide association studies. Nat Rev Genet. 2019 Aug;20(8):467-484. 
* Peterson RE, Kuchenbaecker K, Walters RK, Chen CY, Popejoy AB, Periyasamy S, et al. Genome-wide Association Studies in Ancestrally Diverse Populations: Opportunities, Methods, Pitfalls, and Recommendations. Cell. 2019 Oct 17;179(3):589-603.
* Cano-Gamez E, Trynka G. From GWAS to Function: Using Functional Genomics to Identify the Mechanisms Underlying Complex Diseases. Front Genet. 2020 May 13;11:424. * Schaid DJ, Chen W, Larson NB. From genome-wide associations to candidate causal variants by statistical fine-mapping. Nat Rev Genet. 2018 Aug;19(8):491-504. 
* Lichou F, Trynka G. Functional studies of GWAS variants are gaining momentum. Nat Commun. 2020 Dec 8;11(1):6283.
* Rakyan VK, Down TA, Balding DJ, Beck S. Epigenome-wide association studies for common human diseases. Nat Rev Genet. 2011 Jul 12;12(8):529-41. 
* Li B, Ritchie MD. From GWAS to Gene: Transcriptome-Wide Association Studies and Other Methods to Functionally Understand GWAS Discoveries. Front Genet. 2021 Sep 30;12:713230. 
* Davey Smith G, Hemani G. Mendelian randomization: genetic anchors for causal inference in epidemiological studies. Hum Mol Genet. 2014 Sep 15;23(R1):R89-98.

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# Thank you. Questions?

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Graphics from <img src="./assets/freepik.jpg" style="max-height:20px; vertical-align:middle;"> 
Created: 04-Nov-2022 • James Ashmore • <a href="https://www.zifornd.com/category/omics-bioinformatics">Bioinformatics</a> • <a href="https://www.zifornd.com">Zifo</a>

]